Pharma's commercial operations have undergone a complete digital transformation, leveraging AI and data cloud providers, and customer relationship management (CRM) providers to streamline processes and shift from a product-centric to a customer-centric approach. This has led to personalised marketing and support, improved customer experiences, and reduced costs. Pharma companies are also adopting innovative pricing models, outsourcing non-core functions, and prioritising AI-powered pharmacovigilance and patient support programmes to ensure medication safety, equitable access, and better health outcomes.

The world in 2030 
 

• 360-degree customer view: Pharma companies are using AI  to create a holistic view of their customers, integrating internal and external data to develop a deep understanding of buyer needs and behaviours for targeted engagement.
• Data-driven stakeholder engagement: AI-powered CRMs and real-world data (RWD) enable early and effective communication with stakeholders, demonstrating product value, improving launch while optimising commercialisation strategies.
• Personalised omnichannel experiences: Companies leverage data to segment markets effectively and use dedicated customer relationship teams to deliver tailored omnichannel campaigns, ensuring messages resonate with individual stakeholder needs and accelerating time-to-value.
• Patient-centric approach: Marketing technologies and budgets are shifting towards prioritising the patient experience, with dedicated teams using RWD to understand patient needs and deliver superior support through various touchpoints.
  

Overcoming cross-cutting constraints
 

There are several cross-cutting constraints that could affect the prediction (not having the right skills and talent, funding models, approach to regulation, and data governance in place). The prediction can be realised by turning the constraints into enablers by:

• Cultivating a workforce proficient in data analytics, AI and digital engagement and fostering an agile and entrepreneurial culture than embraces new commercial models and customer-centric approaches
• Optimising commercial strategies with data-driven incentive structures, advanced CRM systems, and a shift towards value-based pricing models that prioritise patient outcomes and affordability
• Balancing innovation with regulatory compliance through robust data privacy measures, proactive risk management, and the use of advanced analytics to ensure transparency and ethical data practices.

Evidence in 2024  
 

• Strategies to improve HCP engagement: a top‑10 biopharma company unlocked 14% higher sales in just 9 months by activating next best action programmes and partnering with Aktana to bridge the gap between strategy and execution. This resulted in sales reps reaching healthcare professionals (HCPs) who had been unresponsive in the past, uncovered opportunities with HCPs who weren’t on their radar before, and pinpointing the right time and right content on digital channels to maximise engagement and proactively identify timely patient alerts.
• Digitalising manufacturing and inventory management: Sanofi has developed an in‑house AI‑enabled yield optimisation solution which learns from experience to achieve consistently higher yield levels. This helps to optimise usage of raw materials, contributing to the company’s environmental objectives, and supporting improved cost efficiency. Adoption within Sanofi’s biopharma supply chain has enabled the team to predict 80% of low inventory positions, allowing them to take mitigating action to quickly address the shortfall.
  

How AI/GenAI might impact pharma’s commercial model
 

• GenAI can analyse patient data to tailor marketing messages, create engaging content, and optimise ad spending by targeting HCPs and patients with personalised, timely information.
• AI can facilitate more successful product launches by analysing market trends and predicting demand; can empower sales reps by personalising outreach to HCPs and patients; and by providing tools like chatbots can enhance interactions with HCPs and patients.
• AI can analyse vast datasets to identify potential drug safety signals faster, enabling proactive risk management and improving pharmacovigilance efforts. 
• GenAI can personalise patient support programmes, leading to better adherence and health outcomes and can also identify individuals who may be at higher risk of experiencing adverse events, enabling proactive intervention and personalised risk management.